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Java image processing ieee projects 2012 @ Seabirds ( Chennai, Bangalore, Hyderabad, Mumbai, Pune)

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  • 1. SEABIRDS IEEE 2012 – 2013 SOFTWARE PROJECTS IN VARIOUS DOMAINS | JAVA | J2ME | J2EE | DOTNET |MATLAB |NS2 |SBGC SBGC24/83, O Block, MMDA COLONY 4th FLOOR SURYA COMPLEX,ARUMBAKKAM SINGARATHOPE BUS STOP,CHENNAI-600106 OLD MADURAI ROAD, TRICHY- 620002Web: www.ieeeproject.inE-Mail: ieeeproject@hotmail.comTrichy ChennaiMobile:- 09003012150 Mobile:- 09944361169Phone:- 0431-4012303
  • 2. SBGC Provides IEEE 2012-2013 projects for all Final Year Students. We do assist the studentswith Technical Guidance for two categories. Category 1 : Students with new project ideas / New or Old IEEE Papers. Category 2 : Students selecting from our project list.When you register for a project we ensure that the project is implemented to your fullestsatisfaction and you have a thorough understanding of every aspect of the project.SBGC PROVIDES YOU THE LATEST IEEE 2012 PROJECTS / IEEE 2013 PROJECTSFOR FOLLOWING DEPARTMENT STUDENTSB.E, B.TECH, M.TECH, M.E, DIPLOMA, MS, BSC, MSC, BCA, MCA, MBA, BBA, PHD,B.E (ECE, EEE, E&I, ICE, MECH, PROD, CSE, IT, THERMAL, AUTOMOBILE,MECATRONICS, ROBOTICS) B.TECH(ECE, MECATRONICS, E&I, EEE, MECH , CSE, IT,ROBOTICS) M.TECH(EMBEDDED SYSTEMS, COMMUNICATION SYSTEMS, POWERELECTRONICS, COMPUTER SCIENCE, SOFTWARE ENGINEERING, APPLIEDELECTRONICS, VLSI Design) M.E(EMBEDDED SYSTEMS, COMMUNICATIONSYSTEMS, POWER ELECTRONICS, COMPUTER SCIENCE, SOFTWAREENGINEERING, APPLIED ELECTRONICS, VLSI Design) DIPLOMA (CE, EEE, E&I, ICE,MECH,PROD, CSE, IT)MBA(HR, FINANCE, MANAGEMENT, HOTEL MANAGEMENT, SYSTEMMANAGEMENT, PROJECT MANAGEMENT, HOSPITAL MANAGEMENT, SCHOOLMANAGEMENT, MARKETING MANAGEMENT, SAFETY MANAGEMENT)We also have training and project, R & D division to serve the students and make them joboriented professionals
  • 3. PROJECT SUPPORTS AND DELIVERABLES Project Abstract IEEE PAPER IEEE Reference Papers, Materials & Books in CD PPT / Review Material Project Report (All Diagrams & Screen shots) Working Procedures Algorithm Explanations Project Installation in Laptops Project Certificate
  • 4. TECHNOLOGY : JAVADOMAIN : IEEE TRANSACTIONS ON IMAGE PROCESSINGS.No. IEEE TITLE ABSTRACT IEEE YEAR 1. A Primal– Loss of information in a wavelet domain can occur 2012 Dual Method during storage or transmission when the images are for Total- formatted and stored in terms of wavelet coefficients. Variation- This calls for image inpainting in wavelet domains. In Based this paper, a variational approach is used to formulate the Wavelet reconstruction problem. We propose a simple but very Domain efficient iterative scheme to calculate an optimal solution Inpainting and prove its convergence. Numerical results are presented to show the performance of the proposed algorithm. 2. A Secret- A new blind authentication method based on the secret 2012 Sharing-Based sharing technique with a data repair capability for Method for grayscale document images via the use of the Portable Authentication Network Graphics (PNG) image is proposed. An of Grayscale authentication signal is generated for each block of a Document grayscale document image, which, together with the Images via the binarized block content, is transformed into several Use of the shares using the Shamir secret sharing scheme. The PNG Image involved parameters are carefully chosen so that as many With a Data shares as possible are generated and embedded into an Repair alpha channel plane. The alpha channel plane is then Capability combined with the original grayscale image to form a PNG image. During the embedding process, the computed share values are mapped into a range of alpha channel values near their maximum value of 255 to yield a transparent stego-image with a disguise effect. In the process of image authentication, an image block is marked as tampered if the authentication signal computed from the current block content does not match that extracted from the shares embedded in the alpha channel plane. Data repairing is then applied to each tampered block by a reverse Shamir scheme after collecting two shares from unmarked blocks. Measures for protecting the security of the data hidden in the alpha channel are also proposed. Good experimental results prove the effectiveness of the proposed method for real applications. 3. Image We investigate the problem of averaging values on 2012 Reduction lattices and, in particular, on discrete product lattices.
  • 5. Using Means This problem arises in image processing when several on Discrete color values given in RGB, HSL, or another coding Product scheme need to be combined. We show how the Lattices arithmetic mean and the median can be constructed by minimizing appropriate penalties, and we discuss which of them coincide with the Cartesian product of the standard mean and the median. We apply these functions in image processing. We present three algorithms for color image reduction based on minimizing penalty functions on discrete product lattices.4. Vehicle We present an automatic vehicle detection system for 2012 Detection in aerial surveillance in this paper. In this system, we Aerial escape from the stereotype and existing frameworks of Surveillance vehicle detection in aerial surveillance, which are either Using region based or sliding window based. We design a pixel Dynamic wise classification method for vehicle detection. The Bayesian novelty lies in the fact that, in spite of performing pixel Networks wise classification, relations among neighboring pixels in a region are preserved in the feature extraction process. We consider features including vehicle colors and local features. For vehicle color extraction, we utilize a color transform to separate vehicle colors and non-vehicle colors effectively. For edge detection, we apply moment preserving to adjust the thresholds of the Canny edge detector automatically, which increases the adaptability and the accuracy for detection in various aerial images. Afterward, a dynamic Bayesian network (DBN) is constructed for the classification purpose. We convert regional local features into quantitative observations that can be referenced when applying pixel wise classification via DBN. Experiments were conducted on a wide variety of aerial videos. The results demonstrate flexibility and good generalization abilities of the proposed method on a challenging data set with aerial surveillance images taken at different heights and under different camera angles.5. Abrupt The robust tracking of abrupt motion is a challenging 2012 Motion task in computer vision due to its large motion Tracking Via uncertainty. While various particle filters and Intensively conventional Markov-chain Monte Carlo (MCMC) Adaptive methods have been proposed for visual tracking, these Markov-Chain methods often suffer from the well-known local-trap Monte Carlo problem or from poor convergence rate. In this paper, we Sampling propose a novel sampling-based tracking scheme for the abrupt motion problem in the Bayesian filtering framework. To effectively handle the local-trap problem,
  • 6. we first introduce the stochastic approximation MonteCarlo (SAMC) sampling method into the Bayesian filtertracking framework, in which the filtering distribution isadaptively estimated as the sampling proceeds, and thus,a good approximation to the target distribution isachieved. In addition, we propose a new MCMC samplerwith intensive adaptation to further improve thesampling efficiency, which combines a density-grid-based predictive model with the SAMC sampling, togive a proposal adaptation scheme. The proposed methodis effective and computationally efficient in addressingthe abrupt motion problem. We compare our approachwith several alternative tracking algorithms, andextensive experimental results are presented todemonstrate the effectiveness and the efficiency of theproposed method in dealing with various types of abruptmotions.

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